{"id":2614979,"url":"https://alion.io/job/eaton-engineer-ml","title":"Engineer - ML","company":{"id":6044,"name":"Eaton","domain":"eaton.com","url":"https://alion.io/company/eaton","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"A","score":90,"open_postings":305,"ghost_share":0.026,"stale_share":0.279,"repost_share":0.079,"time_to_fill_p50_days":41,"computed_at":"2026-10-16T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"middle","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":19000,"max_usd":45000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":25},"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Airflow","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Azure DevOps","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Docker","optional":false},{"name":"Feature Store","optional":false},{"name":"Flink","optional":false},{"name":"GCP","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Hadoop","optional":false},{"name":"Jenkins","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Recommender Systems","optional":false},{"name":"Scikit-learn","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"TensorFlow","optional":false},{"name":"Time Series Forecasting","optional":false}],"status":"live","first_seen_at":"2026-10-12T09:32:51Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-16T16:10:15Z","board_verified":true,"closed_at":null,"days_open":4,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":4},"description":"What you’ll do:\nEaton Corporation’s Center for Intelligent Power has an opening for a Associate Engineer- Machine Learning Operations. The ideal candidate will be responsible for developing and maintaining the infrastructure and tools required to deploy and maintain machine learning models at scale. This position requires understanding in machine learning and software engineering. The candidate will work closely with other teams to make sure the requested features by the businesses are delivered.\nAbout Eaton:\nEaton is power management company with 2018 sales of $21.6 billion. We make what matters work. Everywhere you look-from the technology and machinery that surrounds us, to the critical services and infrastructure that we depend on every day-you’ll find one thing in common. It all relies on power. That’s why Eaton is dedicated to improving people’s lives and the environment with power management technologies that are more reliable, efficient, safe and sustainable. Because this is what matters. We are confident we can deliver on this promise because of the attributes that our employees embody. We’re ethical, passionate, accountable, efficient, transparent, and we’re committed to learning. These values enable us to tackle some of the toughest challenges on the planet, never losing sight of what matters.\"\n- Develop, deploy, and maintain scalable machine learning platforms, infrastructure, and MLOps solutions in cloud environments.\n- Develop, and optimize data engineering pipelines, feature engineering workflows, and CI/CD pipelines for machine learning and AI applications.\n- Build, train, validate, deploy, monitor, and continuously improve machine learning and deep learning models in production.\n- Drive adoption of software engineering best practices, reusable frameworks, templates, coding standards, and automation strategies to reduce development cycle time and improve solution reliability.\n- Troubleshoot model performance, data quality, pipeline reliability, and production issues while ensuring high availability and scalability.\n- Contribute to technical design reviews, architecture discussions, and team knowledge-sharing initiatives.\n- Develop and maintain technical documentation, deployment guides, operational runbooks, and training materials.\n- Evaluate emerging technologies, AI/ML frameworks, cloud services, and industry best practices, and recommend their adoption where appropriate.\nQualifications:\nRequires a minimum of a Bachelor level degree in computer science or equivalent software engineering discipline.\n3-5 years of professional experience in Machine Learning Engineering, MLOps, Data Engineering, or Software Engineering.\nSkills:\nHands-on experience building and deploying machine learning solutions in production environments.\nExperience designing and developing data pipelines, feature stores, and data processing workflows using industry best practices.\nUnderstanding of CI/CD pipelines, Infrastructure as Code (IaC), and automation frameworks for machine learning systems.\nGood understanding of cloud infrastructure such as AWS, Azure, or GCP.\nUnderstanding of containerization and orchestration technologies such as Docker and Kubernetes.\nUnderstanding of machine learning algorithms including regression, classification, clustering, recommendation systems, time-series forecasting, and deep learning.\nExperience with model monitoring, drift detection, performance optimization, and observability frameworks.\nStrong analytical, troubleshooting, and problem-solving skills.\nExcellent communication and stakeholder management skills with the ability to work effectively across cross-functional teams.\nRequired:\nExperience with big data technologies such as Apache Spark, Kafka, Hadoop, Flink, or similar distributed systems.\nExperience developing and maintaining large-scale data engineering pipelines using Python, Spark, Databricks, Airflow, or similar technologies.\nExperience implementing CI/CD pipelines using Azure DevOps, GitHub Actions, Jenkins, or equivalent tools.\nUnderstanding of Docker, Kubernetes, and container-based application deployment.\nStrong understanding of software engineering best practices including object-oriented design, design patterns, version control, testing strategies, code reviews, and secure development practices.\nExperience with model lifecycle management, experiment tracking, feature management, and production model deployment.\nProfessional certifications in Machine Learning, Cloud Technologies, Data Engineering, or MLOps.\nHands-on experience with Databricks, Snowflake, Delta Lake, Feature Stores, or Vector Databases.\nHands-on experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, MLflow, or equivalent platforms.","description_format":"text","description_chars":4755,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Artificial Intelligence","Aerospace Manufacturing","Energy Management","Automotive Components"],"lifecycle":[{"event":"open","at":"2026-10-15T12:00:44Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":3,"expected_fill_days":41,"reasons":["conf:3","velocity","win:early","comp:brand"],"computed_at":"2026-10-16T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/eaton-engineer-ml","json_url":"https://alion.io/job/eaton-engineer-ml.json","meta":{"generated_at":"2026-10-16T17:58:46Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":2819,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-17T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":6044},"rest":"https://alion.io/mcp/rest/get_company?id=6044"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Featon-engineer-ml"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Featon-engineer-ml"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Featon-engineer-ml"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/eaton-engineer-ml\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Featon-engineer-ml"}]}